View representation of spatial data is presented mainly by an electronic map. The electronic map is a visual map, which displays the spatial data on an electronic screen through hardware or software, and is a process of rasterized display of the spatial data on the electronic screen (a view window).
A view is an interface for displaying the spatial data in a view window, which is selected according to a given spatial condition. Conventionally, a process of displaying spatial data by the view is a process of rasterizing the spatial data. The process includes: first, obtaining spatial data meeting a given spatial condition, based on a spatial data index; transmitting the spatial data to a user of the spatial data, i.e., a request transmitting terminal, through a transmission medium; then performing a series of geometric transformation and procession on the spatial data to draw a raster image; and displaying or outputting the raster image on a screen, such as displaying the raster image on a computer screen, printing the raster image on paper or generating an image file to output.
As rapid development of spatial information technology, it becomes possible to obtain high resolution and high precision spatial data. Widespread applications of spatial information based on a network bring both opportunities and challenges to development and application of a Geographic Information System (GIS). Relative to a growth of a bandwidth of an existing network, amount of data for spatial information transmission renders explosive growth. In order to perform a transmission according to demands and reduce network latency, one of important approaches to achieve real time, adaptive and rapid transmission of massive spatial data of a high precision map and to solve display problems thereof is to compress the spatial data and perform a progressive transmission. The spatial data has two basic data structures, i.e., raster data and vector data. A perfect solution may be used to divide raster data into multiple blocks to perform a progressive transmission, whereas block transmission is not adapted to be divided into multiple blocks to perform a transmission due to complex spatial relationships thereof. Therefore, at present, development of research on compression and progressive transmission of spatial data with vector data structure is unsatisfactory and problems are described as following:
1. Problems in Compression:
In an existing method for compressing spatial data, a data type of spatial coordinates is generally converted from float or double to short or int. In this way, data amount is reduced by lowering data precision. However, this method cannot ensure that the compressed spatial data may achieve an unchanged display effect. Furthermore, there is no exact criterion to determine how many data bits are needed to store the compressed spatial data, i.e., there is no exact criterion to determine optimal data bits.
2. Problems in a Progressive Transmission:
By an existing technology, spatial relationships of spatial data can not keep unchanged during the progressive transmission, and a problem of large calculation amount and a low efficiency in progressive transmission can not be solved. Therefore, a preprocessing needs to be performed on original data, to achieve multiscale hierarchical storage. Reprocessing needs to be performed if the original data change. Due to multiscale hierarchical storage of spatial data, if 10 hierarchies are adopted, then the spatial data are stored in 10 hierarchies according to resolutions, and thus a lot of index data and control data are added and storage space is increased. If a resolution of spatial data during display is between resolutions of two hierarchies, the display is distorted and a progressive transmission of a lossless display can not be achieved, i.e., an adaptive progressive transmission can not be achieved. In addition, at present, progressive transmission of coordinate points is adopted in progressive transmission of spatial data. Part of data of certain coordinate points cannot be transmitted progressively according to digits of data. Only usual compression methods, such as Zip compression, are used to compress incremental data, which has a low compression ratio. Spatial relationships between pre-cached spatial data and progressively transmitted incremental data are not considered to further reduce amount of data.
From above, it can not be ensured that the arbitrarily complex vector data and the spatial relations among the vector data display correctly during the compression and the progressive transmission thereof, thus restricting practical utilization of compression and progressive transmission of the spatial data.